Fuzzy control for a MIMO nonlinear system with state constraints

In this paper, an adaptive fuzzy neural network control scheme is developed for a class of multiple-input and multiple-output (MIMO) nonlinear systems with uncertainties and state constraints. Fuzzy neural networks are used to approximate uncertainties in MIMO systems. Integral Lyapunov functions are introduced to address state constraints. By choosing an appropriate integral Lyapunov function, the control performances of the closed-loop system are completely guaranteed. Simulation results for MIMO systems with state constraints are carried out to prove the effectiveness of the designed control.